A Wireless Sensor Network Coverage Optimization Algorithm and Application of Gray Wolf Search with Virtual Force Embedded in Levi's Flight

Abstract

The invention discloses a wireless sensor network coverage optimization algorithm for gray wolf search with virtual force embedded in Levi's flight, comprising: step 1, randomly determining the positions of N nodes in the coverage nodes of the wireless sensor network as the initial positions of real nodes; step 2 , Initialize the solution of the initial position through the modified gray wolf search algorithm embedded in Levi's flight to the virtual node position Step three, search and update the position through the modified gray wolf search algorithm embedded in Levi's flight; Step four, improve the virtual node position Calculate the virtual force with the force algorithm; adjust the position of each group of solution nodes through calculation; step 5, through the survival of the fittest selection rule, retain the better solution obtained by the improved virtual force algorithm and judge whether to update the optimal solution through the better solution of the tth generation Solve α wolf, optimally solve β wolf, and until the specified number of updates is reached. Step 6. Output the optimal solution α wolf as the optimal node position; Step 7. Complete the wireless sensor node deployment through the node matching algorithm.

Description

technical field [0001] The invention relates to the field of wireless sensor coverage optimization, in particular to a wireless sensor network coverage optimization algorithm and application of gray wolf search with virtual force embedded in Levi's flight. Background technique [0002] Although the Wireless sensor network (WSN) was originally designed for military applications, WSN is currently widely used in civilian applications, including vehicle tracking, forest monitoring, earthquake observation, building monitoring, and water resource monitoring. Coverage is an important measure of WSN performance. How to use a limited number of sensor nodes to monitor the coverage target area to the greatest extent has always been one of the hot spots of WSN technology. Wireless sensors are usually randomly scattered in the monitored area, which will cause uneven distribution of nodes and lead to low coverage in the monitored area. Therefore, it is of great significance to improve the...

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Problems solved by technology

[0005] The present invention designs and develops a wireless sensor network coverage optimization algorithm for gray wolf search with virtual force embedded in Levi's flight. The coverage rate of the monitored area is low. At the same time, the present invention will use the VFLGWO algorithm to optimize the WSN node coverage problem, thereby expanding the application field of the LGWO algorithm

[0006] The present invention also designs and develops an application for wireless sensor network coverage optimization. The purpose of the invention is to solve the problem of uneven distribution of nodes when the LGWO algorithm is deployed and applied to WSN nodes, resulting in low coverage of the monitoring area.

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